23 papers · ranked by Valyu relevance
Vaibhav Rupapara, Furqan Rustam, Wajdi Aljedaani, Hina Fatima Shahzad + 2 more
Blood cancer has been a growing concern during the last decade and requires early diagnosis to start proper treatment. The diagnosis process is costly and time-consuming involving medical experts and several tests. Thus, an automatic diagnosis system for its accurate prediction is of significant importance. Diagnosis…
Richmond Addo Danquah
For several years till date, the major issues in terms of solving for classification problems are the issues of Imbalanced data. Because majority of the machine learning algorithms by default assumes all data are balanced, the algorithms do not take into consideration the distribution of the data sample class. The…
Shan Guan, Haiqi Yang, Tongyu Wu
As the cornerstone of transmission and distribution equipment, power transformer plays a very important role in ensuring the safe operation of power system. At present, the technology of dissolved gas analysis (DGA) has been widely used in fault diagnosis of oil-immersed transformer. However, in the actual scene, the…
Luis H. Chia
Credit scoring models face a critical challenge: severe class imbalance, with default rates typically below 10%, which hampers model learning and predictive performance. While synthetic data augmentation techniques such as SMOTE and ADASYN have been proposed to address this issue, the optimal augmentation ratio remains…
Yuheng Lin, Jinlong Shi, Wanyu Xia, Mingjun Zhou + 2 more
Component identification and concentration estimation of a gas mixture component are important for gas detection. However, the accuracy of traditional gas identification will decrease if the sample is not balanced or the number of samples is too few. In this paper, a method based on sample expansion is proposed to…
Authors not listed
The whole world faces a pandemic situation due to the deadly virus, namely COVID-19. It takes considerable time to get the virus well-matured to be traced, and during this time, it may be transmitted among other people. To get rid of this unexpected situation, quick identification of COVID-19 patients is required. We…
Zhewei Chen, Linyue Zhou, Wenwen Yu
Intrusion detection has been a key topic in the field of cyber security, and the common network threats nowadays have the characteristics of varieties and variation. Considering the serious imbalance of intrusion detection datasets will result in low classification performance on attack behaviors of small sample size…
R. Onur Öztornaci, Hamzah Syed, Andrew P. Morris, Bahar Taşdelen
Machine learning (ML) methods for uncovering single nucleotide polymorphisms (SNPs) in genome-wide association study (GWAS) data that can be used to predict disease outcomes are becoming increasingly used in genetic research. Two issues with the use of ML models are finding the correct method for dealing with…
Jacqueline Beinecke, Dominik Heider
Clinical data sets have very special properties and suffer from many caveats in machine learning. They typically show a high-class imbalance, have a small number of samples and a large number of parameters, and have missing values. While feature selection approaches and imputation techniques address the former…
Vasileios Perifanis, Ioanna Michailidi, Giorgos Stamatelatos, George Drosatos + 1 more
'George Drosatos' 'Pavlos S. Efraimidis'] Abstract. In this work, we present a machine learning approach for predicting early dropouts of an active and healthy ageing app. The presented algorithms have been submitted to the IFMBE Scientific Challenge 2022 (wchallenge2022.lst.tfo.upm.es), part of IUPESM WC 2022. We have…
Qi Chen, Wei Huang, Yueyi Zhang, Zhiwei Xiong
The development of learning-based methods has greatly improved the detection of synapses from electron microscopy (EM) images. However, training a model for each dataset is time-consuming and requires extensive annotations. Additionally, it is difficult to apply a learned model to data from different brain regions due…
Ilaria Dutto, Julian Gerhards, Antonio Herrera, Alexandra Junza + 7 more
Adenylosuccinate Lyase (ADSL) functions in the de novo purine biosynthesis pathway. ADSL deficiency (ADSLD) causes numerous neurodevelopmental pathologies, including microcephaly and autism spectrum disorder. ADSLD patients have normal purine nucleotide levels but exhibit accumulation of the dephosphorylated ADSL…
Xiaolong Zhang, Jiajun Du, Fan Liao, Hao Su + 2 more
Understanding intermolecular interactions between Lewis acid and base pairs is of fundamental importance in predicting non-covalent bonding and chemical reactivity. Here we show that an acridinium derivative, a Lewis acid, exhibits various degrees of interactions with Lewis bases of increasing nucleophilicity…
Sooyeon Lee, Huy Kang Kim
—Since with massive data growth, the need for autonomous and generic anomaly detection system is increased. However, developing one stand-alone generic anomaly detection system that is accurate and fast is still a challenge. In this paper, we propose conventional time-series analysis approaches, the Seasonal…
Stephanie Heard, Jaclyn Winter
The adenylation reaction has been a subject of scientific intrigue since it was first recognized as essential to many biological processes, including the homeostasis and pathogenicity of some bacteria and the activation of amino acids for protein synthesis in mammals. Several foundational studies on adenylation (A)…
Nianzhuang Qiu, Chenliang Qian, Tingting Guo, Yaling Wang + 10 more
Dual specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A) plays an essential role in tau and Aβ pathology closely related to Alzheimer’s disease (AD). Accumulative evidence has demonstrated DYRK1A inhibition is able to reduce the pathological features of AD. Nevertheless, there is no approved DYRK1A…
Rumiana Tenchov, Janet Sasso, Qiongqiong Angela Zhou
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, memory loss, and impaired daily functioning. The pathology of AD is marked by the accumulation of amyloid-beta plaques and tau protein tangles in brain, along with neuroinflammation and synaptic dysfunction. Genetic…
Kevin Song, Jianyi Zhang
Alzheimer’s disease (AD) is a systems-level disorder driven by the failure of interconnected biological networks, demanding therapeutic strategies and analytical frameworks that operate beyond single-target paradigms. The multi-target tyrosine kinase inhibitor dasatinib is a promising therapeutic candidate due to its…
Authors not listed
Glutathione S-transferase theta 1 (GSTT1) is essential for metastatic tumour cell dissemination, making it a promising anti-cancer target. This study employed reaction-based de novo design to generate novel competitive GSTT1 inhibitors optimised for both target binding and synthetic accessibility. Using the Synopsis…
Yutaka Matsuda, Natsuki Shikida, Noriko Hatada, Kei Yamada + 10 more
A traceless site-selective conjugation method, “AJICAP-M,” was developed for native antibodies at specific sites using Fc-affinity peptides, focusing on Lys248 or Lys288. It produces antibody-drug conjugates (ADCs) with consistent drug-to-antibody ratios, enhanced stability, and simplified manufacturing. Comparative in…
Jiayi Yang, Samantha B. Riemann, Jinglei Lyu, Sudi Feng + 10 more
Adenovirus infections of immunocompromised humans are a significant source of morbidity and mortality. At present, no drug has been approved by FDA for the treatment of adenovirus infections. A current treatment of such infections is off-label use of an antiviral acyclic nucleotide phosphonate, cidofovir (CDV…
Nicole S. McKay, Brian A. Gordon, Russ C. Hornbeck, Clifford R. Jack + 54 more
The Dominantly Inherited Alzheimer Network (DIAN) Observational Study is an international collaboration studying autosomal dominant Alzheimer disease (ADAD). This rare form of Alzheimer disease (AD) is caused by mutations in the presenilin 1 (PSEN1), presenilin 2 (PSEN2), or amyloid precursor protein (APP) genes. As…
Yuhong Du, Dongxue Wang, Vittorio L. Katis, Elizabeth L. Zoeller + 4 more
The spleen tyrosine kinase (SYK) and high affinity immunoglobulin epsilon receptor subunit gamma (FCER1G) interaction has a major role in the normal innate and adaptive immune responses, but dysregulation of this interaction is implicated in several human diseases, including autoimmune disorders, hematological…